A Primer on FAIR & Open Science

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# A Primer on FAIR & Open Science
## <p>and a brief interlude with GitHub</p>
### <p><strong>Tanya Strydom</strong>🐾<br> PhD Student<br> <a href="https://poisotlab.io">Poisot Lab</a></p>
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<a href="https://twitter.com/tanyas_08"> <span class="citation">@TanyaS_08</span> </a>
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<a href="https://github.com/tanyas08"> <span class="citation">@TanyaS08</span> </a>
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# The Backstory

.center[species interaction networks 🕸 + fancy maths 🧮 | FAIR & Open Science ⚖️ | part-time doodler 🎨 | warm beverage fan ☕]

--
.center[
<br>
Participant of the 5th [Plant Functional Traits Course](https://plantfunctionaltraitscourses.w.uib.no/)

Placed a lot of focus on doing reproducible science

<br>
Inspired [this](https://doi.org/10.1002/ece3.7009) manuscript on how we can incorporate

teaching FAIR and Open Science in 
student training
]

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# What is Open Science?

.center[*A global movement to promote integrity, repeatability, and transparency across all aspects of scientific research*]

.pull-left[
**Which includes:**

- Open access to publications

- Open access to data

- Open source code and data handling
]

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# OS and the Data Lifecycle

.center[Open Science can help extend the lifespan of a dataset e.g. by allowing it to be reused for data synthesis or re-analysis
]

--
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<img src="data:image/png;base64,#img/TheWay.jpeg" width="58%" />
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.center[
But in order for this to happen your data needs to be **usable**
]

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# Make your Science FAIR

.center[***F**indable, **A**ccessible, **I**nteroperable and **R**eproducible*]

.pull-left[

* Sharing data is the first step but not the only one

* **FAIR** principles focus on data usability

* Data are only as good as their documentation

]

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# So What?

1. Open Science will be the 'new normal' and is becoming an expectation for publication and funding

2. Open data leads to increased citations

3. It fosters collaboration and opens doors for what we can achieve with our research

4. It makes your (personal) workflow easier (especially for future you) **and** makes for easier collaborative work/writing
  + The little bit of extra time is worth it - trust me

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# A Quick Case Study<sub style="font-size: medium;">(on what not to do)</sub>

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* My honours file naming 'system'

* The 'amazing' documentation

* To quote the lobster from the *Little Mermaid* "it's a mess"

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# Where to Start Though?

.footnote[[*] Respecting data sharing restrictions and embargoes]

.left-column[data lifecycle.png]

.right-column[
- Think about how you enter your data
  * Follow data and metadata standards (e.g. [DarwinCore](https://www.tdwg.org/))
  * Document it (e.g. README file) think of this as an extensive methods section

- Document data processing and analysis
  * Use code-based workflows
  * Annotate said code
  
  
- Archive data in an accessible way
  * Make as open and findable as possible<sup>*</sup>
  * Include **all** documentation
  * See [here](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005097) for some more tips
  
  
- Do some of your [own research](https://www.fosteropenscience.eu/courses)
]

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# 1. Documenting, Documenting and Documenting

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# If it isn't Documented it Doesn't Exist

**Document all changes to raw data**
+ Ideally after inputting your data into a file<sup>*</sup> it should remain untouched and unchanged. 
+ Using a script based workflow means you keep track of what and how things changed (*sensu lato* a lab book)

.footnote[[*] Ideally using a non propriety format such as .csv or .txt]

**Document the *entire* workflow**
+ Having metadata for variables is good
  + Mandatory I'd argue
+ Documenting how scripts 'work' - even better
  + What happens in each script
  + What order to work with them

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# 2. Annotating code

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# Annotations save lives <sub style="font-size: medium;">(and time)</sub>

Annotating your code by adding comments makes it easier for you (and others) to understand what or why you decided to do what you did

.pull-left[
- Pseudocode can double up as annotations
  * Pseudocoding is a way of writing out your code in 'plain language' before you start coding it up
  
  
- Detail specific changes or reasoning
  * Especially when cleaning or transforming data
  ]

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<img src="data:image/png;base64,#img/annotations.png" width="100%" />]

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# 3. Data Archiving <sub style="font-size: medium;">(with bonus version control)</sub>

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# Get with GitHub

.footnote[[*] I find this also 'forces' me to make sure my code is readable/shareable]

Think of GitHub as a google drive of sorts that you would keep your projects in - the only difference is that it has some bonus features.

* **It's Open Access:** Like a social media profile that people can click on and explore it *i.e.* you can share and showcase your work/packages/projects<sup>*</sup>.
  + This is where your data/analyses can 'live' until needed.

* **It has Version Control:** This means that every time you re-upload a file the older versions are saved (and can be recouped if needed).
  + You can do this [straight from RStudio](https://happygitwithr.com/rstudio-git-github.html)
  + This also facilitates collaboration in a big way (no more email chain!)
      + Everyone has the most up to date version on their device

* **It's Designed for Programming:** Aside form simple storage of files you can design [workflows](https://docs.github.com/en/free-pro-team@latest/actions/learn-github-actions) that run jobs depending on what happens in the repository.

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# A GitHub 'Primer'

1. GitHub is the 'norm' in the world of Open Source  - so if you want to go open go with GitHub

1. [Happy Git and GitHub for the useR](https://happygitwithr.com) is a great starting point if you're interested
  + especially for installing Git on your device (it can be a bit confusing)

1. You can also have private repositories
  * So you can keep your work 'hidden' but still cash in on version control and easier collaborating
  
1. As university students you qualify for a [free pro account](https://education.github.com/pack) - *go for it it*

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# Other Ways to Open your Science

+ Data archiving

+ Pre-registered reports

+ Preprints

+ Social media

Thank You
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Slides available at [https://tanyas08.github.io/Talks/2020_Dec_TUKS/](https://tanyas08.github.io/Talks/2020_Dec_TUKS/index.html)